scholarly journals An Improved Gesture Tracking Algorithm Based On Depth Image Information

2013 ◽  
Author(s):  
Quan Yang
Keyword(s):  
Tracking Algorithm ◽  
Depth Image ◽  
Image Information ◽  
Gesture Tracking

Moving gesture tracking algorithm based on vibe and space-time context

2018 ◽  
Vol 33 (1) ◽  
pp. 92-98
Author(s):  
王 民 WANG Min ◽  
石新源 SHI Xin-yuan ◽  
王稚慧 WANG Zhi-hui ◽  
李泽洋 LI Ze-yang
Keyword(s):  
Space Time ◽  
Tracking Algorithm ◽  
Gesture Tracking

A Track-Based Gesture Recognition Algorithm for Kinect

2015 ◽  
Vol 738-739 ◽  
pp. 334-338 ◽  
Author(s):  
Ying Wang ◽  
Ling Zhang
Keyword(s):  
Gesture Recognition ◽  
Golden Section ◽  
Recognition Algorithm ◽  
Depth Image ◽  
Kinect Sensor ◽  
Recognition Method ◽  
Image Information ◽  
Golden Section Search ◽  
Highly Effective

This paper presents a new gesture track recognition method based on the depth image information received from the Kinect sensor. First, a Kinect sensor is used to obtain the coordinates of a moving arm. Then, the gesture tracks corresponding to these coordinates are analyzed. Matching and recognition of gesture tracks are implemented by performing golden section search. The results show that this track-based method is highly effective in gesture recognition.

A novel edge-enabled SLAM solution using projected depth image information

2019 ◽  
Vol 32 (19) ◽  
pp. 15369-15381 ◽  
Author(s):  
Jian-qiang Li ◽  
Yi-fan Zhang ◽  
Zhuang-zhuang Chen ◽  
Jia Wang ◽  
Min Fang ◽  
...  
Keyword(s):  
Depth Image ◽  
Image Information

scholarly journals An Improved Camshift Tracking Algorithm Based on LiDAR Sensor

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yong Lv ◽  
Hairong Zhu
Keyword(s):  
Information Fusion ◽  
Recognition Rate ◽  
Visual Image ◽  
Tracking Algorithm ◽  
Depth Image ◽  
Interactive System ◽  
Fusion Algorithm ◽  
Interaction Point ◽  
Camshift Algorithm ◽  
Fusion Tracking

Aiming at the problems of inaccurate interaction point position, interaction point drift, and interaction feedback delay in the process of LiDAR sensor signal processing interactive system, a target tracking algorithm is proposed by combining LiDAR depth image information with color images. The algorithm first fuses the gesture detection results of the LiDAR and the visual image and uses the color information fusion algorithm of the Camshift algorithm to realize the tracking of the moving target. The experimental results show that the multi-information fusion tracking algorithm based on this paper has achieved higher recognition rate and better stability and robustness than the traditional fusion tracking algorithm.

Research on Path Tracking Algorithm of Autopilot Vehicle Based on Image Processing

2019 ◽  
Vol 34 (05) ◽  
pp. 2054013
Author(s):  
Yutai Rao ◽  
Fan Yang
Keyword(s):  
Real Time ◽  
Automobile Industry ◽  
Trajectory Tracking ◽  
High Speed ◽  
Control Method ◽  
Visual Navigation ◽  
Tracking Algorithm ◽  
Image Information ◽  
Automatic Driving ◽  
Smart Cars

Smart cars are the result of the combination of the latest technological achievements in the fields of artificial intelligence, sensors, control science, computer, and network technology with the modern automobile industry. Intelligent cars usually have functions, such as automatic shifting, automatic driving, and automatic road condition recognition. The research of intelligent car technology involves many disciplines. This thesis focuses on the field of smart car visual navigation, focusing on image denoising, image information recognition, extraction, and pattern recognition control algorithms. The traditional trajectory tracking algorithm is mainly used in industrial computer or high-performance computer. The computational complexity leads to poor real-time control, and it is easily interfered by external complex terrain environment and internal disordered electromagnetic environment during vehicle driving. In general, on a regular basis, by the image analysis of the driver or the driver information, the image information is proposed using way trace processing technology, vehicle tracking control method and automatic driving rules. The simulation and experimental results show that the proposed control methods and rules used to carry out automatic driving vehicle are feasible. The algorithm reduces the complexity of the algorithm, improves the real-time and stability of the control and finally achieves a good trajectory tracking effect of the car on high-speed automatic driving.

Improved TLD gesture tracking algorithm based on SURF and Camshift

2020 ◽  
Author(s):  
Lisi Wang ◽  
Hua Li ◽  
Cheng Han
Keyword(s):  
Tracking Algorithm ◽  
Gesture Tracking
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